AI Resident

Full Timemid

Milpitas, CAPosted 11 weeks ago

Role Overview

Roboforce is hiring a mid-level AI Resident. This is a full-time role in Milpitas. Full responsibilities, required qualifications, and the apply link are listed in the description below.

Resume Keywords to Include

Make sure these keywords appear in your resume to improve ATS scoring

HTMLTensorFlowPyTorchORNotionCompensationBenefitsWhy

Job description

Why RoboForce

RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company’s robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.

The AI Residency Program

The AI Residency Program is designed for exceptional early-career researchers and engineers who want to tackle some of the hardest problems in robotics and AI. Residents will work alongside a deeply technical team on core challenges in embodied physical intelligence, including Vision-Language-Action (VLA) models, World Models, World Action Models, and 3D foundation models, as well as the full stack of real-world learning—from efficient data collection systems and simulation to reinforcement learning and deployment on physical robots.

This is a hands-on residency for people who want to do ambitious work with real consequences: building learning systems that connect perception, reasoning, and action in service of capable, deployable robots. What makes this program different is the direct connection between research and real-world deployment. Residents work with actual RoboForce robots, iterate quickly between simulation and physical execution, and contribute to systems designed for real use.

The problems are hard, the standards are high, and the goal is to build systems that matter outside the lab.

Research Focus Areas

As an AI Resident, you may contribute across several core areas:

Vision-Language-Action (VLA) models for general-purpose robotic behavior
World Models for predictive modeling, planning, and long-horizon decision-making
World Action Models for jointly modeling action and environment dynamics
Simulation and sim-to-real transfer for scalable training, evaluation, and data generation
Reinforcement learning, imitation learning, and policy optimization for embodied agents
Multimodal learning across vision, language, proprioception, force, and action
Learning systems for manipulation and real-world embodied interaction

What You’ll Do

Conduct research and build systems for embodied physical intelligence
Develop and evaluate methods in VLA, World Models, World Action Models, simulation, and RL
Design and run experiments on robotics tasks involving perception, planning, control, and long-horizon behavior
Build training and evaluation pipelines for large-scale embodied learning systems
Work closely with research and engineering teams to move ideas from prototype to real or simulated robot platforms
Explore how multimodal foundation models can improve robot capability in real deployment settings
Contribute to technical reports, internal research discussions, and, where appropriate, publications

Basic Qualifications

Master’s, or PhD student, recent graduate, or early-career researcher/engineer in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
Experience with modern ML frameworks such as PyTorch, JAX, or TensorFlow
Experience using AI-assisted coding tools and agentic development workflows to prototype, iterate, and build quickly
Ability to implement, debug, and evaluate research ideas in a fast-moving environment
Strong engineering judgment, including the ability to validate, refine, and productionize AI-assisted code

Preferred Qualifications

Rich hands-on experience in robotic manipulation, mobile manipulation, or industrial robotics
Experience training, fine-tuning, or evaluating multimodal or embodied models
Experience with World Models, action-conditioned prediction, model-based learning, planning, or control
Strong hands-on experience with simulation platforms such as Isaac Gym, Isaac Sim, MuJoCo, ManiSkill, Habitat, or similar systems
Experience with reinforcement learning, imitation learning, or post-training for robotic policies
Experience working with real robot hardware, data collection systems, evaluation workflows, or deployment pipelines
Demonstrated technical initiative through research, open-source contributions, or high-impact engineering work

Compensation and Resources

Duration:

3–6 months, full-time

Compensation:

$10,000 monthly salary

Benefits:

Company-provided lunch and dinner, a fully stocked kitchen, and team events
Premium fitness center membership covered by the company

Resources:

Access to large-scale GPU clusters and production-grade infrastructure, with dedicated support to enable fast, uninterrupted experimentation on ambitious robotics and AI workloads

About Roboforce

Roboforce

On-site

9 other open roles at Roboforce on TryApplyNow.

View all 10 roles at Roboforce

Frequently Asked Questions

How do I apply for the AI Resident position at Roboforce?

Use the Apply button above to submit your application directly to Roboforce. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Where is the AI Resident position at Roboforce located?

This position is based in Milpitas. Roboforce has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.

What does a AI Resident at Roboforce earn?

Roboforce has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the AI Resident role at Roboforce posted?

This role was posted on April 22, 2026 (79 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.